All materials contain inherent defects. These are not always harmful, since they can be used to engineer and introduce ...

Material science, at its core, is an interdisciplinary field focusing on the discovery and design of new materials. It combines elements of physics, chemistry and engineering to understand and ...

Engineering economical and scalable processes for direct air capture (DAC) from humid air relies on atomistic modeling to search and identify promising sorbent materials from a va ...

Understanding the properties of different materials is an important step in material design. X-ray absorption spectroscopy (XAS) is an important technique for this, as it reveals detailed insights ...

A machine learning model built on eight material descriptors predicted the specific capacity of nitrogen-doped porous carbon ...

Machine learning doesn't replace human intelligence, but it can outlast human endurance, which makes it a helpful tool for chemistry and materials discovery. Scientists know machine learning models ...

Academics OverviewExplore our degrees, programs, courses, and other enrichment opportunities. All Areas of StudyView a chart of all study areas cross-categorized by degree type. Undergraduate Study ...

A team of Lehigh University researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time—a development that could lead to the creation of ...

Literature searches, simulations, and practical experiments have been part of the materials science toolkit for decades, but the last few years have seen an explosion of machine learning-driven ...

In a new study published in Chemical Science, researchers from the University of Oxford's Department of Chemistry have used machine learning simulations to trace how a common polymer transforms into ...